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rdf:type |
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lifeskim:mentions |
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pubmed:issue |
7
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pubmed:dateCreated |
2010-4-13
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pubmed:abstractText |
Coupling chromatin immunoprecipitation (ChIP) with recently developed massively parallel sequencing technologies has enabled genome-wide detection of protein-DNA interactions with unprecedented sensitivity and specificity. This new technology, ChIP-Seq, presents opportunities for in-depth analysis of transcription regulation. In this study, we explore the value of using ChIP-Seq data to better detect and refine transcription factor binding sites (TFBS). We introduce a novel computational algorithm named Hybrid Motif Sampler (HMS), specifically designed for TFBS motif discovery in ChIP-Seq data. We propose a Bayesian model that incorporates sequencing depth information to aid motif identification. Our model also allows intra-motif dependency to describe more accurately the underlying motif pattern. Our algorithm combines stochastic sampling and deterministic 'greedy' search steps into a novel hybrid iterative scheme. This combination accelerates the computation process. Simulation studies demonstrate favorable performance of HMS compared to other existing methods. When applying HMS to real ChIP-Seq datasets, we find that (i) the accuracy of existing TFBS motif patterns can be significantly improved; and (ii) there is significant intra-motif dependency inside all the TFBS motifs we tested; modeling these dependencies further improves the accuracy of these TFBS motif patterns. These findings may offer new biological insights into the mechanisms of transcription factor regulation.
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pubmed:grant |
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pubmed:commentsCorrections |
http://linkedlifedata.com/resource/pubmed/commentcorrection/20056654-10944202,
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http://linkedlifedata.com/resource/pubmed/commentcorrection/20056654-9788350
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:chemical |
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pubmed:status |
MEDLINE
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pubmed:month |
Apr
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pubmed:issn |
1362-4962
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:volume |
38
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
2154-67
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pubmed:dateRevised |
2011-8-1
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pubmed:meshHeading |
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pubmed:year |
2010
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pubmed:articleTitle |
On the detection and refinement of transcription factor binding sites using ChIP-Seq data.
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pubmed:affiliation |
Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA.
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pubmed:publicationType |
Journal Article,
Research Support, U.S. Gov't, Non-P.H.S.,
Research Support, Non-U.S. Gov't,
Evaluation Studies,
Research Support, N.I.H., Extramural
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